Morphological classifiers

作者：

Highlights：

• Classification framework proposal that uses mathematical morphology.

• Mathematical morphology is sensitive to shapes, density and fractal information in datasets.

• Experiments indicate that morphological approaches are tangible.

• Generated predictive models are fast and visual oriented.

摘要

•Classification framework proposal that uses mathematical morphology.•Mathematical morphology is sensitive to shapes, density and fractal information in datasets.•Experiments indicate that morphological approaches are tangible.•Generated predictive models are fast and visual oriented.

论文关键词：Morphological classifier,Supervised learning,Mathematical morphology,Set theory

论文评审过程：Received 17 June 2016, Revised 8 June 2017, Accepted 11 June 2018, Available online 15 June 2018, Version of Record 10 July 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.06.010